Machine Learning In Biological Sciences

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Machine Learning in Biological Sciences

Author : Shyamasree Ghosh
Publisher : Springer Nature
ISBN 13 : 9811688818
Total Pages : 337 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Machine Learning in Biological Sciences by : Shyamasree Ghosh

Download or read book Machine Learning in Biological Sciences written by Shyamasree Ghosh and published by Springer Nature. This book was released on 2022-05-04 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives an overview of applications of Machine Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences. Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine. This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which forms a major domain of research in the field of biology. It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.

Deep Learning for the Life Sciences

Author : Bharath Ramsundar
Publisher : O'Reilly Media
ISBN 13 : 1492039802
Total Pages : 236 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for the Life Sciences by : Bharath Ramsundar

Download or read book Deep Learning for the Life Sciences written by Bharath Ramsundar and published by O'Reilly Media. This book was released on 2019-04-10 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working

Deep Learning in Science

Author : Pierre Baldi
Publisher : Cambridge University Press
ISBN 13 : 1108845355
Total Pages : 387 pages
Book Rating : 4.1/5 (88 download)

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Book Synopsis Deep Learning in Science by : Pierre Baldi

Download or read book Deep Learning in Science written by Pierre Baldi and published by Cambridge University Press. This book was released on 2021-07 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rigorous treatment of the theory of deep learning from first principles, with applications to beautiful problems in the natural sciences.

Deep Learning in Biology and Medicine

Author : Davide Bacciu
Publisher : World Scientific Publishing Europe Limited
ISBN 13 : 9781800610934
Total Pages : 0 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Deep Learning in Biology and Medicine by : Davide Bacciu

Download or read book Deep Learning in Biology and Medicine written by Davide Bacciu and published by World Scientific Publishing Europe Limited. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.

Machine Learning and IoT

Author : Shampa Sen
Publisher : CRC Press
ISBN 13 : 9781138492691
Total Pages : 354 pages
Book Rating : 4.4/5 (926 download)

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Book Synopsis Machine Learning and IoT by : Shampa Sen

Download or read book Machine Learning and IoT written by Shampa Sen and published by CRC Press. This book was released on 2018-07-02 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine - from storing enormous amounts of biological data to solving complex biological problems and enhancing treatment of various grave diseases.

Machine Learning for Planetary Science

Author : Joern Helbert
Publisher : Elsevier
ISBN 13 : 0128187220
Total Pages : 234 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Machine Learning for Planetary Science by : Joern Helbert

Download or read book Machine Learning for Planetary Science written by Joern Helbert and published by Elsevier. This book was released on 2022-03-22 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as a guide for selecting the right methods and tools for solving a variety of everyday problems in planetary science using machine learning. Illustrating ways to employ machine learning in practice with case studies, the book is clearly organized into four parts to provide thorough context and easy navigation. The book covers a range of issues, from data analysis on the ground to data analysis onboard a spacecraft, and from prioritization of novel or interesting observations to enhanced missions planning. This book is therefore a key resource for planetary scientists working in data analysis, missions planning, and scientific observation. - Includes links to a code repository for sharing codes and examples, some of which include executable Jupyter notebook files that can serve as tutorials - Presents methods applicable to everyday problems faced by planetary scientists and sufficient for analyzing large datasets - Serves as a guide for selecting the right method and tools for applying machine learning to particular analysis problems - Utilizes case studies to illustrate how machine learning methods can be employed in practice

Phenological Research

Author : Irene L. Hudson
Publisher : Springer Science & Business Media
ISBN 13 : 9048133351
Total Pages : 525 pages
Book Rating : 4.0/5 (481 download)

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Book Synopsis Phenological Research by : Irene L. Hudson

Download or read book Phenological Research written by Irene L. Hudson and published by Springer Science & Business Media. This book was released on 2009-11-24 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: As climate change continues to dominate the international environmental agenda, phenology – the study of the timing of recurring biological events – has received increasing research attention, leading to an emerging consensus that phenology can be viewed as an ‘early warning system’ for climate change impact. A multidisciplinary science involving many branches of ecology, geography and remote sensing, phenology to date has lacked a coherent methodological text. This new synthesis, including contributions from many of the world’s leading phenologists, therefore fills a critical gap in the current biological literature. Providing critiques of current methods, as well as detailing novel and emerging methodologies, the book, with its extensive suite of references, provides readers with an understanding of both the theoretical basis and the potential applications required to adopt and adapt new analytical and design methods. An invaluable source book for researchers and students in ecology and climate change science, the book also provides a useful reference for practitioners in a range of sectors, including human health, fisheries, forestry, agriculture and natural resource management.

Artificial Intelligence and Molecular Biology

Author : Lawrence Hunter
Publisher :
ISBN 13 :
Total Pages : 484 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Artificial Intelligence and Molecular Biology by : Lawrence Hunter

Download or read book Artificial Intelligence and Molecular Biology written by Lawrence Hunter and published by . This book was released on 1993 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. The enormous amount of data generated by the Human Genome Project and other large-scale biological research has created a rich and challenging domain for research in artificial intelligence. These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book. Lawrence Hunter is Director of the Machine Learning Project at the National Library of Medicine, National Institutes of Health.

Machine Learning Methods for Ecological Applications

Author : Alan H. Fielding
Publisher : Springer Science & Business Media
ISBN 13 : 1461552893
Total Pages : 265 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Machine Learning Methods for Ecological Applications by : Alan H. Fielding

Download or read book Machine Learning Methods for Ecological Applications written by Alan H. Fielding and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first text aimed at introducing machine learning methods to a readership of professional ecologists. All but one of the chapters have been written by ecologists and biologists who highlight the application of a particular method to a particular class of problem.

Special Topics in Information Technology

Author : Luigi Piroddi
Publisher : Springer Nature
ISBN 13 : 3030859185
Total Pages : 151 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Special Topics in Information Technology by : Luigi Piroddi

Download or read book Special Topics in Information Technology written by Luigi Piroddi and published by Springer Nature. This book was released on 2022-01-01 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.

Hands on Data Science for Biologists Using Python

Author : Yasha Hasija
Publisher : CRC Press
ISBN 13 : 1000345483
Total Pages : 299 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Hands on Data Science for Biologists Using Python by : Yasha Hasija

Download or read book Hands on Data Science for Biologists Using Python written by Yasha Hasija and published by CRC Press. This book was released on 2021-04-08 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Data Science for Biologists using Python has been conceptualized to address the massive data handling needs of modern-day biologists. With the advent of high throughput technologies and consequent availability of omics data, biological science has become a data-intensive field. This hands-on textbook has been written with the inception of easing data analysis by providing an interactive, problem-based instructional approach in Python programming language. The book starts with an introduction to Python and steadily delves into scrupulous techniques of data handling, preprocessing, and visualization. The book concludes with machine learning algorithms and their applications in biological data science. Each topic has an intuitive explanation of concepts and is accompanied with biological examples. Features of this book: The book contains standard templates for data analysis using Python, suitable for beginners as well as advanced learners. This book shows working implementations of data handling and machine learning algorithms using real-life biological datasets and problems, such as gene expression analysis; disease prediction; image recognition; SNP association with phenotypes and diseases. Considering the importance of visualization for data interpretation, especially in biological systems, there is a dedicated chapter for the ease of data visualization and plotting. Every chapter is designed to be interactive and is accompanied with Jupyter notebook to prompt readers to practice in their local systems. Other avant-garde component of the book is the inclusion of a machine learning project, wherein various machine learning algorithms are applied for the identification of genes associated with age-related disorders. A systematic understanding of data analysis steps has always been an important element for biological research. This book is a readily accessible resource that can be used as a handbook for data analysis, as well as a platter of standard code templates for building models.

Data Analytics in Bioinformatics

Author : Rabinarayan Satpathy
Publisher : John Wiley & Sons
ISBN 13 : 111978560X
Total Pages : 433 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Data Analytics in Bioinformatics by : Rabinarayan Satpathy

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Machine Learning in Bioinformatics

Author : Yanqing Zhang
Publisher : John Wiley & Sons
ISBN 13 : 0470397411
Total Pages : 476 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Machine Learning in Bioinformatics by : Yanqing Zhang

Download or read book Machine Learning in Bioinformatics written by Yanqing Zhang and published by John Wiley & Sons. This book was released on 2009-02-23 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.

PlantOmics: The Omics of Plant Science

Author : Debmalya Barh
Publisher : Springer
ISBN 13 : 8132221729
Total Pages : 839 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis PlantOmics: The Omics of Plant Science by : Debmalya Barh

Download or read book PlantOmics: The Omics of Plant Science written by Debmalya Barh and published by Springer. This book was released on 2015-03-18 with total page 839 pages. Available in PDF, EPUB and Kindle. Book excerpt: PlantOmics: The Omics of Plant Science provides a comprehensive account of the latest trends and developments of omics technologies or approaches and their applications in plant science. Thirty chapters written by 90 experts from 15 countries are included in this state-of-the-art book. Each chapter describes one topic/omics such as: omics in model plants, spectroscopy for plants, next generation sequencing, functional genomics, cyto-metagenomics, epigenomics, miRNAomics, proteomics, metabolomics, glycomics, lipidomics, secretomics, phenomics, cytomics, physiomics, signalomics, thiolomics, organelle omics, micro morphomics, microbiomics, cryobionomics, nanotechnology, pharmacogenomics, and computational systems biology for plants. It provides up to date information, technologies, and their applications that can be adopted and applied easily for deeper understanding plant biology and therefore will be helpful in developing the strategy for generating cost-effective superior plants for various purposes. In the last chapter, the editors have proposed several new areas in plant omics that may be explored in order to develop an integrated meta-omics strategy to ensure the world and earth’s health and related issues. This book will be a valuable resource to students and researchers in the field of cutting-edge plant omics.

Gene Expression Data Analysis

Author : Pankaj Barah
Publisher : CRC Press
ISBN 13 : 1000425754
Total Pages : 276 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Gene Expression Data Analysis by : Pankaj Barah

Download or read book Gene Expression Data Analysis written by Pankaj Barah and published by CRC Press. This book was released on 2021-11-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and the biological sciences

Machine Learning - A Journey To Deep Learning: With Exercises And Answers

Author : Andreas Miroslaus Wichert
Publisher : World Scientific
ISBN 13 : 9811234078
Total Pages : 641 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Machine Learning - A Journey To Deep Learning: With Exercises And Answers by : Andreas Miroslaus Wichert

Download or read book Machine Learning - A Journey To Deep Learning: With Exercises And Answers written by Andreas Miroslaus Wichert and published by World Scientific. This book was released on 2021-01-26 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)

The Deep Learning Revolution

Author : Terrence J. Sejnowski
Publisher : MIT Press
ISBN 13 : 026203803X
Total Pages : 354 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Deep Learning Revolution by : Terrence J. Sejnowski

Download or read book The Deep Learning Revolution written by Terrence J. Sejnowski and published by MIT Press. This book was released on 2018-10-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.